A Feature Recognition Method of Underwater Slender Body Based on Multi-bright Spot Cluster Analysis

A cluster analysis and slender body technology, applied in character and pattern recognition, instruments, calculations, etc., can solve problems such as poor robustness, unsuitable K-means algorithm, outlier points, etc., and achieve reliable results

Active Publication Date: 2021-03-19
INST OF ACOUSTICS CHINESE ACAD OF SCI
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

One of the disadvantages of the K-means clustering algorithm is that it is less robust to outliers
The underwater environment is more complex, and the measurement noise is non-Gaussian and unknown, resulting in outliers often appearing, so the data obtained in the underwater environment is not suitable for the K-means algorithm

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Feature Recognition Method of Underwater Slender Body Based on Multi-bright Spot Cluster Analysis
  • A Feature Recognition Method of Underwater Slender Body Based on Multi-bright Spot Cluster Analysis
  • A Feature Recognition Method of Underwater Slender Body Based on Multi-bright Spot Cluster Analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] Other characteristics, characteristics and advantages of the present invention will be more apparent after the following detailed description of the embodiments of the present invention by way of examples in conjunction with the accompanying drawings.

[0046] For a large-scale target with slender body characteristics, when the target width is ignored, the target is regarded as a line segment, and all the reflection centers of its bright spots are collinear, that is, they are all located on the longitudinal axis of the target. The focus of the present invention is the estimation of the reflection center of a large target in a clustering problem with constraint characteristics.

[0047] In order to determine the motion characteristics of underwater slender body characteristics, at least two centers of bright spots are required to determine the longitudinal axis baseline of an underwater target. The increase of the number of bright spot centers, on the one hand, can incre...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an underwater slender body feature recognition method based on multi-bright spot cluster analysis. The method includes the following steps: calculating the length and motion direction of the underwater slender body target using the bright spot spatial distribution; combining the cluster analysis method, The expected maximum value EM algorithm under constraints is used to obtain the cluster center of the target cluster points, and the course and length of the target can be estimated accordingly. The present invention adopts the EM algorithm with constraints, and utilizes the multi-bright spot information to estimate the advancing direction (course) and scale of the underwater target with a slender shape; and the method has the characteristics of simplicity, ease of operation, and reliable operation .

Description

technical field [0001] The invention relates to the field of underwater vehicles, in particular to a feature recognition method for underwater slender bodies based on multi-bright spot cluster analysis Background technique [0002] Underwater target feature recognition has always been one of the research focuses in the field of sonar signal processing. Its main purpose is to obtain underwater target characteristics, including position information, speed, heading direction and size, etc. Sonar is usually used to detect underwater targets. The tracking algorithm of the underwater maneuvering target calculates the relative distance, direction and relative speed of the target according to the echo characteristics of the target, and then estimates the motion characteristics of the target according to the target motion equation and filtering algorithm. However, due to the particularity of the underwater environment, the estimation error of the distance, azimuth and radial velocit...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/2321
Inventor 刘宇朱晓萌马晓川鄢社锋侯朝焕
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap